Quarto Report

UNICEF Data Analysis: Youth Unemployment and Child Immunization

Introduction

This report presents the data analysis of two important dimensions of human development: youth unemployment and child immunization.
Using UNICEF-sourced data-sets, we first investigate employment patterns among youth across countries, and subsequently transition to examining trends in childhood vaccination as a proxy for healthcare access.

Both employment opportunities and healthcare delivery are crucial indicators of social development, and understanding these aspects helps build a more holistic view of progress across regions.

library(tidyverse)
library(plotly)
library(sf)
library(rnaturalearth)
library(rnaturalearthdata)
indicator1 <- read_csv("unicef_indicator_1.csv")
# head(indicator1)

BAR CHART of Youth Unemployment by Gender

ggplot(indicator1, aes(x = sex, y = obs_value, fill = sex)) +
  geom_bar(stat = "identity") +
  geom_text(aes(label = round(obs_value, 2)), 
            vjust = -0.5, size = 3) +
  scale_fill_manual(values=c("Male" = "royalblue", "Female" = "lightpink"))+
  theme_minimal() +
  labs(
    title = "Youth Unemployment Rate: Male vs Female",
    x = "Gender",
    y = "Unemployment Rate (%)",
    fill = "Gender"
  ) +
  theme(
    plot.title = element_text(hjust = 0.5, size = 14, face = "bold"),
    axis.text = element_text(size = 10),
    axis.title = element_text(size = 11)
  )

Scatter Plot with Linear Regression Line

ggplot(indicator1, aes(x = obs_value, y = time_period)) +
  geom_point(color = "red") +
  geom_smooth(method = "lm", se = FALSE, color = "black") +
  theme_minimal() +
  labs(
    title = "Observation Value vs Time Period",
    x = "Observation Value",
    y = "Year"
  )

Youth Unemployment Distribution over the world

fig <- plot_ly(indicator1,
               type = "choropleth",
               locations = ~alpha_3_code,
               locationmode = "ISO-3",
               z = ~obs_value,
               text = ~paste(
                 "<b>Country:</b>", country, "<br>",
                 "<b>Value:</b>", round(obs_value, 2)
               ),
               colorscale = "Viridis",
               marker = list(line = list(color = "white", width = 1)))
fig <- fig %>% layout(
  title = list(
    text = "<b>Youth Unemployment Rate by Country</b>",
    font = list(size = 20),
    x = 0.5
  ),
  geo = list(
    projection = list(type = "natural earth"),
    showframe = FALSE,
    showcoastlines = TRUE,
    coastlinecolor = "gray"
  ),
  margin = list(t = 80)
)
fig

Human Development

After examining youth unemployment patterns, here is a bit extended analysis towards another key dimension of human development: child immunization. Childhood vaccination rates serve as an important proxy for healthcare access, infrastructure quality, and social well-being in countries.
The following section visualizes trends in child immunization rates across years based on another UNICEF dataset.

indicator2 <- read_csv("unicef_indicator_2.csv")

Child Vaccination Trends

vaccination_trend <- indicator2 %>%
  group_by(time_period) %>%
  summarise(avg_vaccination = mean(obs_value, na.rm = TRUE))
ggplot(vaccination_trend, aes(x = time_period, y = avg_vaccination)) +
  geom_line(color = "royalblue", linewidth = 1.5) +
  geom_point(color = "firebrick", size = 2) +
  theme_minimal() +
  labs(
    title = "Global Average Child Vaccination Rate Over Time",
    x = "Year",
    y = "Average Vaccination Rate (%)"
  ) +
  theme(plot.title = element_text(hjust = 0.5))

Conclusion

This report presents a dual exploration of human development through employment and healthcare lenses.

In the first story, youth unemployment patterns were analyzed, revealing notable gender disparities and regional differences based on UNICEF data.
However, limitations such as lack of multi-year country-level data restricted deeper time trend analyses.

In the second story, child immunization rates were studied as a complementary indicator of development.
The time series visualization highlights improvements in healthcare access globally, although regional disparities likely remain.

Together, these analyses demonstrate the interconnection of employment opportunities and healthcare outcomes in shaping broader human development trajectories.